{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "# 正态性检验\n",
    "\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from scipy.stats import norm\n",
    "from scipy.stats import lognorm\n",
    "from scipy.stats import t"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 正态分布"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5,0,'不同方差, 相同均值')"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "xs_nd = np.linspace(start=-4, stop=4, num=100)\n",
    "\n",
    "fig, (ax1, ax2) = plt.subplots(nrows=1, ncols=2)\n",
    "fig.set_figwidth(12)\n",
    "\n",
    "ax1.plot(xs_nd, norm.pdf(xs_nd, loc=-1, scale=1), color='r', label='norm(-1, 1)')\n",
    "ax1.plot(xs_nd, norm.pdf(xs_nd, loc=0, scale=1), color='g', label='norm(0, 1)')\n",
    "ax1.plot(xs_nd, norm.pdf(xs_nd, loc=1, scale=1), color='b', label='norm(1, 1)')\n",
    "\n",
    "ax1.legend()\n",
    "ax1.set_ylabel('f(x)')\n",
    "ax1.set_xlabel('相同方差, 不同均值')\n",
    "\n",
    "ax2.plot(xs_nd, norm.pdf(xs_nd, loc=0, scale=0.5), color='r', label='norm(0, 0.5)')\n",
    "ax2.plot(xs_nd, norm.pdf(xs_nd, loc=0, scale=1), color='g', label='norm(0, 1)')\n",
    "ax2.plot(xs_nd, norm.pdf(xs_nd, loc=0, scale=2), color='b', label='norm(0, 2)')\n",
    "\n",
    "ax2.legend()\n",
    "ax2.set_ylabel('f(x)')\n",
    "ax2.set_xlabel('不同方差, 相同均值')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 对数正态分布"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fc10d29e940>]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "s = 0.954\n",
    "xs_nd_2 = np.linspace(start=lognorm.ppf(0.01, s), stop=lognorm.ppf(0.95, s), num=100)\n",
    "plt.figure(figsize=(6, 4))\n",
    "plt.plot(xs_nd_2, lognorm.pdf(xs_nd_2, s))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 正态分布和t分布对比"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(array(0.), array(1.66666667), array(0.), array(6.))\n",
      "(array(0.), array(1.66666667), array(0.), array(0.))\n",
      "[0.37960669] [0.30901936]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df = 5\n",
    "sigma = np.sqrt(5/3)\n",
    "xs_nd_3 = np.linspace(start=t.ppf(0.01, df), stop=t.ppf(0.99, df), num=100)\n",
    "plt.figure(figsize=(8,4))\n",
    "plt.plot(xs_nd_3, t.pdf(xs_nd_3, df), color='g', lw=1)\n",
    "plt.plot(xs_nd_3, norm.pdf(xs_nd_3, 0, sigma), color='b', lw=1)\n",
    "ax = plt.gca()\n",
    "ax.spines['right'].set_color('none')\n",
    "ax.spines['top'].set_color('none')\n",
    "ax.spines['bottom'].set_position(('data', 0))\n",
    "ax.spines['left'].set_position(('data', 0))\n",
    "\n",
    "# 方差相同, 峰度不同, t(5)的峰度要高\n",
    "print(t.stats(df, moments='mvsk'))\n",
    "print(norm.stats(loc=0, scale=sigma, moments='mvsk'))\n",
    "print(t.pdf([0], df), norm.pdf([0], 0, sigma))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 偏度和峰度"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.0 1.0 0.0 0.0\n",
      "0.0 3.614211636916553 5.406631446568272 79.18946566730335\n"
     ]
    }
   ],
   "source": [
    "mean, variance, skewness, kurtosis = norm.stats(moments=\"mvsk\")\n",
    "print(mean, variance, skewness, kurtosis)\n",
    "mean_1, variance, skewness, kurtosis = lognorm.stats(0.95, moments=\"mvsk\")\n",
    "print(mean, variance, skewness, kurtosis)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(0.9978201985359192, 0.7721009254455566)\n",
      "AndersonResult(statistic=0.23339859489851733, critical_values=array([0.571, 0.651, 0.781, 0.911, 1.083]), significance_level=array([15. , 10. ,  5. ,  2.5,  1. ]))\n",
      "KstestResult(statistic=0.02463268388262485, pvalue=0.9220074815302887)\n",
      "NormaltestResult(statistic=0.7607542261109828, pvalue=0.6836035647681039)\n"
     ]
    },
    {
     "data": {
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      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "### 正态性检验\n",
    "from scipy.stats import shapiro\n",
    "from scipy.stats import anderson\n",
    "from scipy.stats import kstest\n",
    "from scipy.stats import normaltest\n",
    "\n",
    "np.random.seed(12345678)\n",
    "data = norm.rvs(loc=0, scale=1, size=500)\n",
    "# data = [2.7, -1.2, -1.0, 0, 0.7, 2.0, 3,7, -0.6, 0.8, -0.3]\n",
    "\n",
    "plt.figure()\n",
    "plt.hist(data)\n",
    "\n",
    "# W-test\n",
    "print(shapiro(data))\n",
    "\n",
    "# AD检验\n",
    "print(anderson(data, dist='norm'))\n",
    "\n",
    "# KS-test or D\n",
    "print(kstest(data, cdf='norm'))\n",
    "\n",
    "# Normal-test\n",
    "print(normaltest(data, axis=0))"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
